System, method, and non-transitory computer-readable storage media for recommending merchants

ABSTRACT

A computer system for recommending merchants to a candidate cardholder is provided. The computer system includes a memory device and a processor. The processor receives transaction information for a plurality of cardholders from a payment network. The transaction information includes data relating to purchases made by the cardholders at a plurality of merchants, where the purchases satisfy a first criteria. The processor also receives candidate cardholder preference information for at least one of the merchants input by the candidate cardholder. The processor further determines a merchant rank for each merchant based on the received transaction information and the candidate cardholder preference information, and determines a neutral merchant rank for each merchant based on the received transaction information and neutral cardholder preferences of the plurality of cardholders. The processor also determines a merchant score for each of the plurality of merchants by comparing the merchant rank to the neutral merchant rank.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims priority to U.S. patentapplication Ser. No. 16/593,420 filed on Oct. 4, 2019, entitled “SYSTEM,METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIA FORRECOMMENDING MERCHANTS”, which is a continuation of and claims priorityto U.S. patent application Ser. No. 13/797,400 filed on Mar. 12, 2013,entitled “SYSTEMS AND METHODS FOR RECOMMENDING MERCHANTS”, which areboth hereby incorporated herein by reference in their entirety.

BACKGROUND OF THE DISCLOSURE

The field of the disclosure relates generally to methods and systems forrecommending merchants and, more particularly, to methods and systemsfor recommending merchants to a transaction payment cardholder based atleast in part on the cardholder's past transaction history and thecardholder's merchant preferences.

Consumers today are provided with an increasing number of segments ofentertainment choices available, as well as, an increasing number ofmerchants available in each segment. A segment is a group of merchantsoffering a similar entertainment experience, such as a dining segment,an events segment, a night club segment, and an activities segment. Forexample, in many cities, consumers have hundreds if not thousands ofrestaurant options when they desire to eat. Moreover, even when therestaurant options are narrowed by restaurant category or cuisine, theremay still be an inconveniently large number of restaurant optionspresented to the consumer. Additionally, new restaurants may becomeavailable without the consumer's knowledge.

To address these issues, various known methods exist that providerestaurant recommendations to consumers. For example, Internet websitesexist that enable consumers to provide restaurant reviews or score therestaurant, as well as, provide descriptive information (e.g., averageprices, type of cuisine) about the restaurant. Often times, consumerscan provide their comments and information for a restaurant in additionto a professional reviewer, thereby providing additional opinions forconsumers. One problem that arises with relying on reviews of otherconsumers when selecting a restaurant is that some consumers havedifferent preferences than other consumers, which can make the reviewsand/or score for a restaurant unreliable for certain consumers.Additionally, in some instances, consumers are more likely to post areview based on a bad experience at a restaurant than they are to post apositive review, which can bias recommendations for other consumers.

Moreover, merchants may want to aid a consumer's decision by offeringincentives, such as reward points, discounts, and special offers toconsumers. Consumers have the option of searching numerous websites or“friending” numerous merchants in an effort to make more informedentertainment decisions. However, the websites are often not objectiveand their reputations are often not objective, and friending numerousmerchant results in time-consuming searching through the friendedmerchant's website.

BRIEF DESCRIPTION OF THE DISCLOSURE

In one embodiment, a computer system for recommending merchants to acandidate cardholder is provided. The computer system includes a memorydevice in communication with a processor. The processor is programmed toreceive transaction information for a plurality of cardholders from apayment network. The transaction information includes data relating topurchases made by the cardholders at a plurality of merchants. Thepurchases satisfying a first criteria. The processor receives candidatecardholder preference information for at least one of the merchantsinput by the candidate cardholder. The computer system determines amerchant rank for each merchant based on the received transactioninformation and the candidate cardholder preference information, anddetermines a neutral merchant rank for each merchant based on thereceived transaction information and neutral cardholder preferences ofthe plurality of cardholders. The computer system then determines amerchant score for each of the plurality of merchants by comparing themerchant rank to the neutral merchant rank.

In another embodiment, a computer-implemented method is provided forrecommending at least one merchant of a plurality of merchants to acandidate cardholder using a merchant analytic (MA) computer system. TheMA computer system is in communication with a memory device. The methodincludes receiving transaction information for a plurality ofcardholders including the candidate cardholder from a payment network.The transaction information includes data relating to purchases made bythe cardholders at the plurality of merchants, wherein the purchasessatisfy during a predetermined time period and within a predeterminedgeographical region. The method also includes receiving candidatecardholder preference information for at least one of the plurality ofmerchants, wherein the candidate cardholder preference information isinput by the candidate cardholder using a cardholder computing device.The method determines a merchant rank for each merchant based on thereceived transaction information and the candidate cardholder preferenceinformation, and determines a neutral merchant rank for each merchantbased on the received transaction information and neutral cardholderpreferences associated with the cardholders. The method uses the MAcomputer system to determine a merchant score for each merchant bycomparing the merchant rank to the neutral merchant rank.

In yet another embodiment, one or more computer-readable storage mediaprovided that include computer-executable instructions embodied thereonfor recommending at least one merchant of a plurality of merchants to acandidate cardholder. When executed by at least one processor, thecomputer-executable instructions cause the processor to receivetransaction information for a plurality of cardholders including thecandidate cardholder from a payment network. The transaction informationincludes data relating to purchases made by the cardholders at aplurality of merchants. The purchases satisfy a first criteria. Theprocessor receives candidate cardholder preference information for atleast one of the plurality of merchants. The processor also determines amerchant rank for each merchant based on the received transactioninformation and the candidate cardholder preference information. Theprocessor further determines a neutral merchant rank for each merchantbased on the received transaction information and neutral cardholderpreferences associated with the cardholders. The processor determines amerchant score for each of the plurality of merchants by comparing themerchant rank to the neutral merchant rank.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1-17 show exemplary embodiments of the methods and systemsdescribed herein.

FIG. 1 is a schematic diagram illustrating an example multi-partypayment card industry system for enabling ordinary payment-by-cardtransactions in which merchants and card issuers do not necessarily havea one-to-one relationship.

FIG. 2 is a simplified block diagram of an example merchant analyticcomputer system including a plurality of computer devices including auser device having a merchant recommender application in accordance withone example embodiment of the present invention.

FIG. 3 is an expanded block diagram of an example embodiment of a serverarchitecture of the merchant analytic computer system including theplurality of computer devices in accordance with one example embodimentof the present invention.

FIG. 4 illustrates an example configuration of a client system shown inFIGS. 2 and 3 .

FIG. 5 illustrates an example configuration of a server system shown inFIGS. 2 and 3 .

FIG. 6 is a block diagram showing an operation of the merchant analyticcomputer system shown in FIG. 2 .

FIG. 7 is a flow diagram of an example method of recommending merchantsto a candidate cardholder using the merchant analytic computer systemshown in FIG. 2 coupled to a user device having a merchant recommenderapplication stored thereon.

FIG. 8 is a block diagram showing the process by which the merchantanalytic computer system creates a matrix of merchant associations.

FIG. 9 is a screen shot of an initial screen of the merchant recommenderapplication shown in FIG. 2 that may be used by a cardholder tointerface with the merchant analytic computer system shown in FIG. 2 .

FIG. 10 is a screen shot displayed within the merchant recommenderapplication shown in FIG. 2 showing a filter screen that may be used bya cardholder to interface with the merchant analytic computer systemshown in FIG. 2 .

FIG. 11 is a screen shot displayed within the merchant recommenderapplication shown in FIG. 2 showing a filter manually screen that may beused by a cardholder to interface with the merchant analytic computersystem shown in FIG. 2 .

FIG. 12 is a screen shot displayed within the merchant recommenderapplication shown in FIG. 2 showing a list of recommended merchantsgenerated by the merchant analytic computer system shown in FIG. 2 .

FIG. 13 is a screen shot displayed within the merchant recommenderapplication shown in FIG. 2 showing a merchant detail screen.

FIG. 14 is a screen shot of a merchant portal that interfaces between amerchant using a client system and the merchant analytic computer systemboth shown in FIG. 2 .

FIG. 15 is a screen shot of a customer details tab of the merchantportal shown in FIG. 14 .

FIG. 16 is a screen shot of a loyalty tab of the merchant portal shownin FIG. 14 .

FIG. 17 is a screen shot of an offers tab of the merchant portal shownin FIG. 14 .

DETAILED DESCRIPTION OF THE DISCLOSURE

The following detailed description illustrates embodiments of theinvention by way of example and not by way of limitation. Thedescription clearly enables one skilled in the art to make and use thedisclosure, describes several embodiments, adaptations, variations,alternatives, and uses of the disclosure, including what is presentlybelieved to be the best mode of carrying out the disclosure. Thedisclosure is described as applied to an example embodiment, namely,methods and systems for providing cardholders objective and reputableinformation for making entertainment decisions among numerous availablemerchants. More specifically, the disclosure describes a merchantanalytic computer system (also referred to as “MA computer system”)configured to collect transaction data associated with a paymentcardholder, apply cardholder preferences, and recommend at least onemerchant to the cardholder that the cardholder may be interested intransacting business with. The MA computer system is in communicationwith a user device having a merchant recommender application (alsoreferred to as “recommender app”) stored thereon such that a user (e.g.,a cardholder) can input preferences to be considered by the MA computersystem, and view output from the MA computer system. The output includesrecommendations for merchants that match or compare similarly to othermerchants frequented by user.

The MA computer system is configured to recommend a merchant to acardholder. In the example embodiment, the MA computer system isconfigured for use with a payment card processing network such as, forexample, an interchange network. The MA computer system includes amemory device and a processor in communication with the memory deviceand is programmed to communicate with the payment network to receivetransaction information for a plurality of cardholders. The paymentnetwork is configured to process payment card transactions between themerchant and its acquirer bank, and the cardholder and their issuerbank. Transaction information includes data relating to purchases madeby cardholders at various merchants during a predetermined time periodand within a predetermined geographical region. In some embodiments, theplurality of purchases made by the cardholders are related to each otheras being in the same market segment, for example, but not limited to, adining segment, an events segment, a night club segment, or anactivities segment.

In the example embodiment, for cardholders that transact at two or moremerchants of the plurality of merchants during the predetermined timeperiod, the MA computer system creates a matrix of merchant associationsfor the plurality of merchants indicating the number of transactionsbetween each merchant combination and the cardholders. For eachcardholder that has transacted at multiple merchants within thespecified segment, the MA computer system updates the association matrixwith the transaction information. More specifically, a counter isassociated with each merchant within the matrix. For each pair ofmerchants visited by each cardholder, the MA computer system incrementsthe counter associated with those merchants. Accordingly, the more oftena cardholder of the plurality of cardholders transacts with a merchant,the more associations that merchant will obtain within the matrix.

The MA computer system is also programmed to receive candidatecardholder preference information from a candidate cardholder includedwithin the plurality of cardholders for one or more merchant of theplurality of merchants. Candidate cardholder preference information isinputted to the MA computer system by the candidate cardholder using arecommender application stored on a cardholder computing device, such asa Smartphone having a recommender app stored thereon. In one embodiment,candidate cardholder preference information is obtained by the MAcomputer system analyzing historical transaction data associated withthe candidate cardholder for merchants transacted with. In anotherembodiment, the candidate cardholder manually selects at least onemerchant within the recommender app. The list of merchants is generatedby the MA computer system based on a geographical region selectable bythe candidate cardholder. In another embodiment, the cardholder inputs“friends” associated with the cardholder on a social networking websiteand/or from experts subscribed to by the cardholder on a socialnetworking website. In the example embodiment, candidate cardholderpreference information may include results from surveys, Internetwebsite scraping, solicited and unsolicited opinion data, satisfactionscale input, and/or other ranking acquisition methods. Moreover,candidate cardholder preference information may relate to an overallexperience with a merchant.

Based on the candidate cardholder preference information, the MAcomputer system creates a candidate cardholder preference vector. Thecandidate cardholder preference vector represents a measurement of thecandidate cardholder's preference for one merchant relative to at leastone other merchant of the plurality of merchants. In one embodiment,cardholder merchant preferences are associated with a score for eachmerchant. For example, the preference may be measured on a scale of 1 to10, or on a 5-star scale. In another embodiment, a value of one isassociated with each merchant selected by the candidate cardholder froma list and aggregated. In a further embodiment, each merchant isassociated with a magnitude based on a gratuity amount inferred from thehistorical transaction information. Regardless of the preferencemeasurement chosen, in some embodiments, the MA computer systemnormalizes the candidate cardholder preference vector such that eachmerchant is given a value, and the values for the plurality of merchantssums to one, which provides a scaled candidate cardholder preferencevector that is biased based on the candidate cardholder's merchantpreferences.

In the example embodiment, the MA computer system applies the candidatecardholder preference vector to the matrix of merchant associations todetermine a merchant ranking vector. The merchant ranking vector isassociated with the candidate cardholder preference information andincludes a merchant rank associated with each merchant of the pluralityof merchants. The merchant rank represents a measure of generalpopularity of each merchant relative to the plurality of merchants thatis adjusted according to the candidate cardholder preferenceinformation.

The MA computer system then creates and applies a neutral preferencevector to the matrix of merchant associations to determine a neutralmerchant ranking vector. The neutral preference vector includes genericpreference information that is equal for each merchant of the pluralityof merchants. The neutral merchant ranking vector includes a neutralmerchant rank associated with each merchant of the plurality ofmerchants. The neutral merchant rank represents a measure of generalpopularity of each merchant relative to the plurality of merchants amongthe plurality of cardholders.

The MA computer system compares the neutral merchant ranking vector tothe merchant ranking vector to determine a merchant score vector for thecandidate cardholder. The merchant score vector includes a merchantscore indicating the difference between the merchant rank and theneutral merchant rank associated with each merchant of the plurality ofmerchants. The merchant score represents a measure of recommendation foreach merchant of the plurality of merchants determined by the MAcomputer system for the candidate cardholder.

In the example embodiment, the MA computer system sorts the merchantscore vector in descending order based on the merchant score associatedwith each merchant of the plurality of merchants. More specifically, inthe example embodiment, the merchant having the highest merchant scoreis placed first in the merchant score vector and the merchant having thelowest merchant score is placed last in the merchant score vector. TheMA computer system then provides a list of recommended merchants to thecandidate cardholder using the recommender app, wherein the list isbased on the sorted merchant score vector.

A technical effect of the systems and methods described herein isachieved by performing at least one of the following steps: (a)receiving, by the MA computer system, transaction information for aplurality of cardholders from a payment network, wherein the transactioninformation includes data relating to purchases made by the plurality ofcardholders at a plurality of merchants during a predetermined timeperiod and within a predetermined geographical region (or some othercriteria); (b) for cardholders that transact at two or more merchants ofthe plurality of merchants during the predetermined time period,creating a matrix of merchant associations for the plurality ofmerchants indicating the number of transactions between each merchantcombination and the cardholders; (c) receiving, from a candidatecardholder included within the plurality of cardholders, candidatecardholder preference information for one or more merchants of theplurality of merchants, the candidate cardholder preference informationinputted using a recommender app stored on a cardholder computingdevice; (d) based on the candidate cardholder preference information,creating a candidate cardholder preference vector representing ameasurement of the candidate cardholder's preference for one merchantrelative to at least one other merchant; (e) applying the candidatecardholder preference vector to the matrix of merchant associations todetermine a merchant ranking vector, wherein the merchant ranking vectoris associated with the candidate cardholder and includes a merchant rankassociated with each merchant of the plurality of merchants; (f)applying a neutral preference vector to the matrix of merchantassociations to determine a neutral merchant ranking vector, wherein theneutral preference vector includes generic preference information thatis equal for each merchant of the plurality of merchants and wherein theneutral merchant ranking vector includes a neutral merchant rankassociated with each merchant of the plurality of merchants; (g)comparing the neutral merchant ranking vector to the merchant rankingvector to determine a merchant score vector for the candidatecardholder, wherein the merchant score vector includes a merchant scoreindicating the difference between the merchant rank and the neutralmerchant rank associated with each merchant of the plurality ofmerchants, and wherein the merchant score represents a level ofrecommendation determined for the candidate cardholder; (h) sorting themerchant score vector in descending order based on the merchant scoreassociated with each merchant of the plurality of merchants; and (i)providing a list of recommended merchants to the candidate cardholder,wherein the list is based on the sorted merchant score vector.

As used herein, the terms “transaction card,” “financial transactioncard,” and “payment card” refer to any suitable transaction card, suchas a credit card, a debit card, a prepaid card, a charge card, amembership card, a promotional card, a frequent flyer card, anidentification card, a prepaid card, a gift card, and/or any otherdevice that may hold payment account information, such as mobile phones,Smartphones, personal digital assistants (PDAs), key fobs, and/orcomputers. Each type of transactions card can be used as a method ofpayment for performing a transaction.

In one embodiment, a computer program is provided, and the program isembodied on a computer readable medium. In an exemplary embodiment, thesystem is executed on a single computer system, without requiring aconnection to a sever computer. In a further exemplary embodiment, thesystem is being run in a Windows® environment (Windows is a registeredtrademark of Microsoft Corporation, Redmond, Washington). In yet anotherembodiment, the system is run on a mainframe environment and a UNIX®server environment (UNIX is a registered trademark of AT&T located inNew York, New York). The application is flexible and designed to run invarious different environments without compromising any majorfunctionality. In some embodiments, the system includes multiplecomponents distributed among a plurality of computing devices. One ormore components may be in the form of computer-executable instructionsembodied in a computer-readable medium. The systems and processes arenot limited to the specific embodiments described herein. In addition,components of each system and each process can be practiced independentand separate from other components and processes described herein. Eachcomponent and process can also be used in combination with otherassembly packages and processes.

The following detailed description illustrates embodiments of theinvention by way of example and not by way of limitation. It iscontemplated that the invention has general application to processingfinancial transaction data by a third party in industrial, commercial,and residential applications.

As used herein, an element or step recited in the singular and proceededwith the word “a” or “an” should be understood as not excluding pluralelements or steps, unless such exclusion is explicitly recited.Furthermore, references to “example embodiment” or “one embodiment” ofthe present invention are not intended to be interpreted as excludingthe existence of additional embodiments that also incorporate therecited features.

FIG. 1 is a schematic diagram illustrating an example multi-partytransaction card industry system 20 for enabling ordinarypayment-by-card transactions in which merchants 24 and card issuers 30do not need to have a one-to-one special relationship. Embodimentsdescribed herein may relate to a transaction card system, such as acredit card payment system using the MasterCard® interchange network.The MasterCard® interchange network is a set of proprietarycommunications standards promulgated by MasterCard InternationalIncorporated® for the exchange of financial transaction data and thesettlement of funds between financial institutions that are members ofMasterCard International Incorporated®. (MasterCard is a registeredtrademark of MasterCard International Incorporated located in Purchase,New York).

In a typical transaction card system, a financial institution called the“issuer” issues a transaction card, such as a credit card, to a consumeror cardholder 22, who uses the transaction card to tender payment for apurchase from a merchant 24. To accept payment with the transactioncard, merchant 24 must normally establish an account with a financialinstitution that is part of the financial payment system. This financialinstitution is usually called the “merchant bank,” the “acquiring bank,”or the “acquirer.” When cardholder 22 tenders payment for a purchasewith a transaction card, merchant 24 requests authorization from amerchant bank 26 for the amount of the purchase. The request may beperformed over the telephone, but is usually performed through the useof a point-of-sale terminal, which reads cardholder's 22 accountinformation from a magnetic stripe, a chip, or embossed characters onthe transaction card and communicates electronically with thetransaction processing computers of merchant bank 26. Alternatively,merchant bank 26 may authorize a third party to perform transactionprocessing on its behalf. In this case, the point-of-sale terminal willbe configured to communicate with the third party. Such a third party isusually called a “merchant processor,” an “acquiring processor,” or a“third party processor.”

Using an interchange network 28, computers of merchant bank 26 ormerchant processor will communicate with computers of an issuer bank 30to determine whether cardholder's 22 account 32 is in good standing andwhether the purchase is covered by cardholder's 22 available creditline. Based on these determinations, the request for authorization willbe declined or accepted. If the request is accepted, an authorizationcode is issued to merchant 24.

When a request for authorization is accepted, the available credit lineof cardholder's 22 account 32 is decreased. Normally, a charge for apayment card transaction is not posted immediately to cardholder's 22account 32 because bankcard associations, such as MasterCardInternational Incorporated®, have promulgated rules that do not allowmerchant 24 to charge, or “capture,” a transaction until goods areshipped or services are delivered. However, with respect to at leastsome debit card transactions, a charge may be posted at the time of thetransaction. When merchant 24 ships or delivers the goods or services,merchant 24 captures the transaction by, for example, appropriate dataentry procedures on the point-of-sale terminal. This may includebundling of approved transactions daily for standard retail purchases.If cardholder 22 cancels a transaction before it is captured, a “void”is generated. If cardholder 22 returns goods after the transaction hasbeen captured, a “credit” is generated. Interchange network 28 and/orissuer bank 30 stores the transaction card information, such as a typeof merchant, amount of purchase, date of purchase, in a database 120(shown in FIG. 2 ).

After a purchase has been made, a clearing process occurs to transferadditional transaction data related to the purchase among the parties tothe transaction, such as merchant bank 26, interchange network 28, andissuer bank 30. More specifically, during and/or after the clearingprocess, additional data, such as a time of purchase, a merchant name, atype of merchant, purchase information, cardholder account information,a type of transaction, itinerary information, information regarding thepurchased item and/or service, and/or other suitable information, isassociated with a transaction and transmitted between parties to thetransaction as transaction data, and may be stored by any of the partiesto the transaction. In the exemplary embodiment, when cardholder 22purchases travel, such as airfare, a hotel stay, and/or a rental car, atleast partial itinerary information is transmitted during the clearanceprocess as transaction data. When interchange network 28 receives theitinerary information, interchange network 28 routes the itineraryinformation to database 120.

For debit card transactions, when a request for a personalidentification number (PIN) authorization is approved by the issuer,cardholder's account 32 is decreased. Normally, a charge is postedimmediately to cardholder's account 32. The payment card associationthen transmits the approval to the acquiring processor for distributionof goods/services or information, or cash in the case of an automatedteller machine (ATM).

After a transaction is authorized and cleared, the transaction issettled among merchant 24, merchant bank 26, and issuer bank 30.Settlement refers to the transfer of financial data or funds amongmerchant's 24 account, merchant bank 26, and issuer bank 30 related tothe transaction. Usually, transactions are captured and accumulated intoa “batch,” which is settled as a group. More specifically, a transactionis typically settled between issuer bank 30 and interchange network 28,and then between interchange network 28 and merchant bank 26, and thenbetween merchant bank 26 and merchant 24.

FIG. 2 is a simplified block diagram of an example processing system 100including a plurality of computer devices including a user device havinga merchant recommender application in accordance with one exampleembodiment of the present invention. In the example embodiment, system100 may be used for performing payment-by-card transactions received aspart of processing the financial transaction. In addition, system 100 isa payment processing system that includes a merchant analytic (MA)computer system 121 configured to provide merchant recommendation datato a computing device using a merchant recommender application 119stored thereon. As described below in more detail, MA computer system121 is configured to receive transaction data and cardholder preferenceinformation, and recommend a list of merchants to a particularcardholder via merchant recommender application 119 based on thereceived information.

More specifically, in the example embodiment, system 100 includes aserver system 112, and a plurality of client sub-systems, also referredto as client systems 114, connected to server system 112. In oneembodiment, client systems 114 are computers including a web browser,such that server system 112 is accessible to client systems 114 usingthe Internet or some other network connection configured for processingpayment card transactions. Client systems 114 are interconnected to theInternet through many interfaces including a network, such as a localarea network (LAN) or a wide area network (WAN), dial-in-connections,cable modems, and special high-speed Integrated Services Digital Network(ISDN) lines. Client systems 114 could be any device capable ofinterconnecting to the Internet including a web-based phone, PDA, orother web-based connectable equipment.

System 100 also includes point-of-sale (POS) terminals 115, which may beconnected to client systems 114 and may be connected to server system112. POS terminals 115 are interconnected to the Internet through manyinterfaces including a network, such as a LAN or a WAN,dial-in-connections, cable modems, wireless modems, and specialhigh-speed ISDN lines. POS terminals 115 could be any device capable ofinterconnecting to the Internet and including an input device capable ofreading information from a consumer's financial transaction card.

A database server 116 is connected to database 120, which containsinformation on a variety of matters, as described below in greaterdetail. In one embodiment, centralized database 120 is stored on serversystem 112 and can be accessed by potential users at one of clientsystems 114 by logging onto server system 112 through one of clientsystems 114 or by a merchant recommender application 119 stored on acardholder computing device 118. In an alternative embodiment, database120 is stored remotely from server system 112 and may benon-centralized.

Database 120 may include a single database having separated sections orpartitions or may include multiple databases, each being separate fromeach other. Database 120 may store transaction data generated as part ofsales activities conducted over the processing network including datarelating to merchants, account holders or customers, issuers, acquirers,purchases made. Database 120 may also store account data including atleast one of a cardholder name, a cardholder address, an account number,and other account identifier. Database 120 may also store merchant dataincluding a merchant identifier that identifies each merchant registeredto use the network, and instructions for settling transactions includingmerchant bank account information. Database 120 may also store purchasedata associated with items being purchased by a cardholder from amerchant, and authorization request data.

System 100 also includes at least one cardholder computing device 118,which is configured to communicate with at least one of POS terminals115, client systems 114 and server system 112. In the exampleembodiment, cardholder computing device 118 is associated with orcontrolled by a cardholder making a purchase using system 100.Cardholder computing device 118 is interconnected to the Internetthrough many interfaces including a network, such as a LAN or WAN,dial-in-connections, cable modems, wireless modems, and specialhigh-speed ISDN lines. Cardholder computing device 118 may be any devicecapable of interconnecting to the Internet including a web-based phone,smartphone, PDA, iPhone® (iPhone is a registered trademark of Apple,Incorporated located in Cupertino, California), Android® device (Androidis a registered trademark of Google Incorporated located in MountainView, California), and/or any device capable of executing storedcomputer-readable instructions. Cardholder computing device 118 isconfigured to communicate with POS terminals 115 using various outputsincluding, for example, Bluetooth communication, radio frequencycommunication, near field communication, network-based communication,and the like.

In the example embodiment, cardholder computing device 118 includesmerchant recommender application 119, or recommender app 119.

Recommender app 119 interfaces between a cardholder using cardholdercomputing device 118 and MA computer system 121. More specifically,recommender app 119 receives and transmits cardholder transactioninformation and cardholder preference information input by thecardholder to MA computer system 121 either directly or through server112. Transaction information may include a payment card number, anaccount number and/or any other data relating to purchases made by acardholder.

In the example embodiment, cardholder computing device 118 may initiatea transaction by transmitting payment card data to merchant POS device115 or a cardholder can initiate a transaction by swiping a payment cardat POS device 115. The transaction can then be processed, and settled,in a typical multi-party payment card industry system, e.g., system 20(shown in FIG. 1 ). As described below, transaction data can then betransmitted to cardholder device 118 and displayed along with merchantrecommendations through recommender app 119.

In the example embodiment, one of client systems 114 may be associatedwith acquirer bank 26 (shown in FIG. 1 ) while another one of clientsystems 114 may be associated with issuer bank 30 (shown in FIG. 1 ).POS terminal 115 may be associated with a participating merchant 24(shown in FIG. 1 ) or may be a computer system and/or mobile system usedby a cardholder making an on-line purchase or payment. Server system 112may be associated with interchange network 28. In the exemplaryembodiment, server system 112 is associated with a network interchange,such as interchange network 28, and may be referred to as an interchangecomputer system. Server system 112 may be used for processingtransaction data. In addition, client systems 114 and/or POS terminal115 may include a computer system associated with at least one of anonline bank, a bill payment outsourcer, an acquirer bank, an acquirerprocessor, an issuer bank associated with a transaction card, an issuerprocessor, a remote payment system, and/or a biller. Further, in theexample embodiment, MA computer system 121 is included in or is incommunication with server system 112. In various embodiments, MAcomputer system 121 may be associated with a standalone processor or maybe associated with a separate third party provider in a contractualrelationship with interchange network 28 and configured to perform thefunctions described herein. Accordingly, each party involved inprocessing transaction data are associated with a computer system shownin system 100 such that the parties can communicate with one another asdescribed herein.

FIG. 3 is an expanded block diagram of an exemplary embodiment of aserver architecture of a processing system 122 including other computerdevices in accordance with one embodiment of the present invention.Components in system 122, identical to components of system 100 (shownin FIG. 2 ), are identified in FIG. 3 using the same reference numeralsas used in FIG. 2 . System 122 includes server system 112, clientsystems 114, and POS terminals 115. Server system 112 further includesdatabase server 116, a transaction server 124, a web server 126, a faxserver 128, a directory server 130, and a mail server 132. A storagedevice 134 is coupled to database server 116 and directory server 130.Servers 116, 124, 126, 128, 130, and 132 are coupled in a LAN 136. Inaddition, a system administrator's workstation 138, a user workstation140, and a supervisor's workstation 142 are coupled to LAN 136.Alternatively, workstations 138, 140, and 142 are coupled to LAN 136using an Internet link or are connected through an Intranet.

Each workstation, 138, 140, and 142 is a personal computer having a webbrowser. Although the functions performed at the workstations typicallyare illustrated as being performed at respective workstations 138, 140,and 142, such functions can be performed at one of many personalcomputers coupled to LAN 136. Workstations 138, 140, and 142 areillustrated as being associated with separate functions only tofacilitate an understanding of the different types of functions that canbe performed by individuals having access to LAN 136.

Server system 112 is configured to be communicatively coupled to variousindividuals, including employees 144 and to third parties, e.g., accountholders, customers, auditors, developers, consumers, merchants,acquirers, issuers, etc., 146 using an ISP Internet connection 148. Thecommunication in the exemplary embodiment is illustrated as beingperformed using the Internet, however, any other WAN type communicationcan be utilized in other embodiments, i.e., the systems and processesare not limited to being practiced using the Internet. In addition, andrather than WAN 150, local area network 136 could be used in place ofWAN 150.

In the example embodiment, any authorized individual having aworkstation 154 can access system 122. At least one of the clientsystems includes a manager workstation 156 located at a remote location.Workstations 154 and 156 are personal computers having a web browser.Also, workstations 154 and 156 are configured to communicate with serversystem 112. Furthermore, fax server 128 communicates with remotelylocated client systems, including a client system 156 using a telephonelink. Fax server 128 is configured to communicate with other clientsystems 138, 140, and 142 as well.

In the example embodiment, MA computer system 121 is in communicationwith server system 112 and is in wireless communication with clientsystems 114, POS terminals 115, and/or cardholder computing device 118.Moreover, in the example embodiment, cardholder computing device 118 isin wireless communication with POS terminals 115 or, alternatively, maybe in wireless communication with server system 112 or client systems114 and other workstations through a network connection.

FIG. 4 illustrates an example configuration of a user system 202operated by a user 201, such as cardholder 22 (shown in FIG. 1 ). Usersystem 202 may include, but is not limited to, client systems 114, 138,140, and 142, POS terminal 115, user device 118 including recommenderapp 119 (shown in FIG. 2 ), workstation 154, and manager workstation156. In the example embodiment, user system 202 includes a processor 205for executing instructions. In some embodiments, executable instructionsare stored in a memory area 210. Processor 205 may include one or moreprocessing units, for example, a multi-core configuration. Memory area210 is any device allowing information such as executable instructionsand/or written works to be stored and retrieved. Memory area 210 mayinclude one or more computer readable media.

User system 202 also includes at least one media output component 215for presenting information to user 201. Media output component 215 isany component capable of conveying information to user 201. In someembodiments, media output component 215 includes an output adapter suchas a video adapter and/or an audio adapter. An output adapter isoperatively coupled to processor 205 and operatively couplable to anoutput device such as a display device, a liquid crystal display (LCD),organic light emitting diode (OLED) display, or “electronic ink”display, or an audio output device, a speaker or headphones.

In some embodiments, user system 202 includes an input device 220 forreceiving input from user 201. Input device 220 may include, forexample, a keyboard, a pointing device, a mouse, a stylus, a touchsensitive panel, a touch pad, a touch screen, a gyroscope, anaccelerometer, a position detector, or an audio input device. A singlecomponent such as a touch screen may function as both an output deviceof media output component 215 and input device 220. User system 202 mayalso include a communication interface 225, which is communicativelycouplable to a remote device such as server system 112. Communicationinterface 225 may include, for example, a wired or wireless networkadapter or a wireless data transceiver for use with a mobile phonenetwork, Global System for Mobile communications (GSM), 3G, or othermobile data network or Worldwide Interoperability for Microwave Access(WIMAX).

Stored in memory area 210 are, for example, computer readableinstructions for providing a user interface to user 201 via media outputcomponent 215 and, optionally, receiving and processing input from inputdevice 220. A user interface may include, among other possibilities, aweb browser and client application. Web browsers enable users, such asuser 201, to display and interact with media and other informationtypically embedded on a web page or a website from server system 112. Aclient application allows user 201 to interact with a server applicationfrom server system 112.

FIG. 5 illustrates an exemplary configuration of a server system 275such as server system 112 (shown in FIGS. 2 and 3 ). Server system 275may include, but is not limited to, database server 116, applicationserver 124, web server 126, fax server 128, directory server 130, andmail server 132.

Server system 275 includes a processor 280 for executing instructions.Instructions may be stored in a memory area 285, for example. Processor280 may include one or more processing units (e.g., in a multi-coreconfiguration) for executing instructions. The instructions may beexecuted within a variety of different operating systems on the serversystem 275, such as UNIX, LINUX, Microsoft Windows®, etc. It should alsobe appreciated that upon initiation of a computer-based method, variousinstructions may be executed during initialization. Some operations maybe required in order to perform one or more processes described herein,while other operations may be more general and/or specific to aparticular programming language (e.g., C, C#, C++, Java, or othersuitable programming languages, etc.).

Processor 280 is operatively coupled to a communication interface 290such that server system 275 is capable of communicating with a remotedevice such as a user system or another server system 275. For example,communication interface 290 may receive requests from client system 114via the Internet, as illustrated in FIGS. 2 and 3 .

Processor 280 may also be operatively coupled to a storage device 134.Storage device 134 is any computer-operated hardware suitable forstoring and/or retrieving data. In some embodiments, storage device 134is integrated in server system 275. For example, server system 275 mayinclude one or more hard disk drives as storage device 134. In otherembodiments, storage device 134 is external to system 275 and may beaccessed by a plurality of server systems 275. For example, storagedevice 134 may include multiple storage units such as hard disk drivesor solid state drives in a redundant array of inexpensive disks (RAID)configuration. Storage device 134 may include a storage area network(SAN) and/or a network attached storage (NAS) system.

In some embodiments, processor 280 is operatively coupled to storagedevice 134 via a storage interface 295. Storage interface 295 is anycomponent capable of providing processor 280 with access to storagedevice 134. Storage interface 295 may include, for example, an AdvancedTechnology Attachment (ATA) adapter, a Serial ATA (SATA) adapter, aSmall Computer System Interface (SCSI) adapter, a RAID controller, a SANadapter, a network adapter, and/or any component providing processor 280with access to storage device 134.

Memory area 285 may include, but are not limited to, random accessmemory (RAM) such as dynamic RAM (DRAM) or static RAM (SRAM), read-onlymemory (ROM), erasable programmable read-only memory (EPROM),electrically erasable programmable read-only memory (EEPROM), andnon-volatile RAM (NVRAM). The above memory types are exemplary only, andare thus not limiting as to the types of memory usable for storage of acomputer program.

FIG. 6 is a block diagram showing operation of MA computer system 121(shown in FIG. 2 ). MA computer system 121 is configured receivetransaction data for a plurality of cardholders transacting with aplurality of merchants, receive cardholder preferences, and output alist of merchants recommended by MA computer system 121 based on thereceived data. In the example embodiment, MA computer system 121 is incommunication with a payment network, such as payment card interchangenetwork 28 (shown in FIG. 1 ), for receiving transaction data. MAcomputer system 121 includes a memory device 600 and a processor 602 incommunication with memory device 600.

In the example embodiment, MA computer system 121 is programmed tocommunicate with payment network 28 to receive transaction information604 for a plurality of payment cardholders. Payment network 28 isconfigured to process payment card transactions between merchants 24associated with merchant banks 26, and cardholders 22 associated withissuer banks 30. Payment card transaction information 604 includes datarelating to purchases made by a plurality of cardholders 22 at aplurality of merchants 24 during a predetermined time period and withina predetermined geographical region or some other criteria applied tothe data. In some embodiments, the plurality of purchases made bycardholder 22 are related to each other as being in the same marketsegment, for example, but not limited to a dining segment, an eventssegment, a night club segment, or an activities segment. The diningsegment may include all purchases made at restaurants and food servicemerchants. The events segment may include all purchases that relate toconcerts, sporting, or cultural events. The night club segment mayinclude dance clubs and casinos. The activities segment may includeamusement parks, and attractions.

MA computer system 121 is also programmed to receive candidatecardholder preference information 606. Candidate cardholder preferenceinformation 606 may be received by: (i) MA computer system 121 analyzinghistorical transaction information for candidate cardholder 22; (ii)manual input from cardholder 22; (iii) extract preference informationfrom “friends” 608 of cardholder 22 on a social networking website;and/or (iv) extract preference information from experts 610 subscribedto by cardholder 22 on a social networking website. Candidate cardholderpreference information 606 may further include results from surveys,Internet website scraping, solicited and unsolicited opinion data,satisfaction scale input, and/or other ranking acquisition methods.Moreover, candidate cardholder preference information 606 may relate toan overall experience with merchants 24, or may include informationrelating to any aspect of an experience with merchant 24.

MA computer system 121 is further programmed to receive merchantdescriptive information 612 from merchant 24 or from a third partyservice 614. Merchant descriptive information 612 includes informationrelating to location, hours of operation, upcoming events, entertainmentprovided, and advertising and promotional information. Merchantdescriptive information 612 is stored in database 120 (shown in FIG. 2 )associated with interchange network 28.

In the example embodiment, MA computer system 121 is also programmed todetermine location information for each of the plurality of merchantsrelative to a predetermined selectable location and/or a currentlocation 616 of cardholder 22. For example, a cardholder that usescardholder computing device 118 (shown in FIG. 2 ) having a GPScapability 618 can use the determined location information to order alisting of merchants by distance from a current location of cardholder22 or a location chosen by cardholder 22, for example, a hotel in adistant city where cardholder 22 will be staying during an upcomingtrip.

In the example embodiment, MA computer system 121 is also programmed todetermine a merchant score for each of the plurality of merchants 24using the received transaction information 604 and the receivedcardholder preference information 606. The merchant score indicates adifference between a merchant rank and a neutral merchant rankassociated with each merchant of the plurality of merchants, as will bedescribed in more detail herein. The merchant score represents a levelof recommendation (e.g., on a scale from 1 to 100 with 100 being themost recommended merchant for that particular cardholder) determined fora particular cardholder 22. In an alternate embodiment, MA computersystem 121 is programmed to determine merchant scores for the pluralityof merchants using at least one manually selected merchant 24 selectedby candidate cardholder 22 from a list of the plurality of merchants 24.After determining the merchant scores of merchants 24, MA computersystem 121 sorts the plurality of merchants 24 in descending order basedon the merchant scores and provides a list 620 of recommended merchantsto cardholder computing device 118, where it is displayed to candidatecardholder 22 via recommender app 119, as is described in further detailherein. Where the MA computer system 121 outputs a list of recommendedmerchants, it does so by taking into account a particular cardholder'spreferences. As used herein, this particular cardholder may be referredto as a “candidate cardholder”.

FIG. 7 is a flow diagram of an example method 700 of recommending atleast one merchant of a plurality of merchants to a candidate cardholderusing a computer device coupled to a database. In the exampleembodiment, method 700 may be implemented by MA computer system 121(shown in FIG. 2 ).

In the example embodiment, the MA computer system receives 702transaction information for a plurality of payment cardholders from apayment network. The payment network is configured to process paymentcard transactions between a merchant and a cardholder. The transactioninformation includes data relating to purchases made by a plurality ofcardholders at a plurality of merchants during a predetermined timeperiod and within a predetermined geographical region. In someembodiments, the purchases made by the plurality of cardholders arerelated to each other as being in the same market segment, for example,but not limited to a dining segment, an events segment, a night clubsegment, or an activities segment.

In the example embodiment, for cardholders that transact at two or moremerchants of the plurality of merchants, the MA computer system creates704 a matrix of merchant associations for the plurality of merchantsindicating the number of transactions between each merchant combinationand the cardholders. For each cardholder that has transacted at multiplemerchants within the specified segment, the MA computer system updatesthe association matrix with the transaction information. Morespecifically, a counter is associated with each merchant within thematrix. For each pair of merchants visited by each cardholder, the MAcomputer system increments 706 the counter associated with thosemerchants. Accordingly, the more often a cardholder of the plurality ofcardholders transacts with a merchant, the more associations thatmerchant will obtain within the matrix.

For example, FIG. 8 is a block diagram showing the process by which theMA computer system creates a matrix of merchant associations. Initially,the MA computer system determines which merchants associated with aspecified segment are located within a predetermined region (e.g., acity or a specified radius from a location) specified by the cardholderand inputs those merchants into a matrix 800. In the example embodiment,matrix 800 includes merchants a, b, c, d, e, and f. The MA computersystem obtains transaction data 802 for cardholders that have transactedwith merchants a, b, c, d, e, and/or f during a specified time period804 or window of observation 804. The transaction data is provided by apayment network.

Using the transaction data, the MA computer system populates matrix 800to obtain a matrix of merchant associations 806. In the exampleembodiment, a cardholder must have transacted with two or more ofmerchants a, b, c, d, e, and f to be counted in matrix 806. Thisfacilitates reducing an effect of cardholder bias toward a singlemerchant. In the example embodiment, for each pair of merchants acardholder has transacted with, the MA computer system increments acounter associated with the merchant pair. For example, because 1^(st)cardholder transacted with merchants a and b, increments a value storedin block (a, b) of matrix 806 by a value of one. Additionally, block (b,a) is incremented by one. As shown in transaction data 802, both 2^(nd)and 4^(th) cardholders transacted with merchants e and b. Accordingly,the MA computer system increments blocks (e, b) and (b, e) by a value oftwo in matrix 806. Once complete with all of the transaction data,matrix of merchant associations 806 provides a measure of theassociations between each pair of merchants based on how often eachcardholder transacts with both merchants of the pair. Additionally,matrix of merchant associations 806 illustrates a popularity of eachmerchant relative to the other merchants based on historical data, freefrom cardholder bias.

Referring back to FIG. 7 , after creating the merchant associationmatrix, the MA computer system receives 708 candidate cardholderpreference information from a candidate cardholder included within theplurality of cardholders for one or more merchant of the plurality ofmerchants. Candidate cardholder preference information is inputted tothe MA computer system by the candidate cardholder using a recommenderapp, for example, recommender app 119 (shown in FIGS. 2 and 3 ) storedon a cardholder computing device, such as a Smartphone. In oneembodiment, candidate cardholder preference information is obtained bythe MA computer system by analyzing historical transaction dataassociated with the candidate cardholder for merchants transacted with.In another embodiment, to provide candidate cardholder preferenceinformation, the candidate cardholder manually selects at least onemerchant from a list of merchants within a predetermined geographicalregion. The list of merchants is generated by the MA computer systembased on a geographical region selectable by the candidate cardholder.In another embodiment, candidate cardholder preference information isobtained from “friends” associated with the candidate cardholder on asocial networking website, and/or from experts subscribed to by thecardholder on a social networking website. Candidate cardholderpreference information may include results from surveys, Internetwebsite scraping, solicited and unsolicited opinion data, satisfactionscale input, and/or other ranking acquisition methods. Moreover,candidate cardholder preference information may relate to an overallexperience with a merchant.

In the example embodiment, based on the cardholder merchant preferences,the MA computer system creates 710 a candidate cardholder preferencevector. The candidate cardholder preference vector represents ameasurement of the candidate cardholder's preference for one merchantrelative to at least one other merchant of the plurality of merchants.In one embodiment, cardholder merchant preferences are associated with ascore for each merchant. For example, the preference may be measured ona scale of 1 to 10, or on a 5-star scale. In another embodiment, a valueof one is associated with each merchant selected by the candidatecardholder from a list and aggregated. In a further embodiment, eachmerchant is associated with a magnitude based on a gratuity amountinferred from the historical transaction information. Regardless of thepreference measurement chosen, the MA computer system normalizes thecandidate cardholder preference vector such that each merchant is givena value, and the values for the plurality of merchants sums to one,which provides a scaled candidate cardholder preference vector that isbiased based on the candidate cardholder's merchant preferences.

After obtaining the merchant preference vector, the MA computer systemapplies 712 the candidate cardholder preference vector to the matrix ofmerchant associations to determine a merchant ranking vector. Themerchant ranking vector is associated with the candidate cardholderpreference information and includes a merchant rank associated with eachmerchant of the plurality of merchants. The merchant rank represents alevel or a measure of general popularity of each merchant relative tothe plurality of merchants that is adjusted according to the candidatecardholder preference information.

The MA computer system then creates and applies 714 a neutral preferencevector to the matrix of merchant associations to determine a neutralmerchant ranking vector. The neutral preference vector includes genericpreference information that is equal for each merchant of the pluralityof merchants. The neutral merchant ranking vector includes a neutralmerchant rank associated with each merchant of the plurality ofmerchants. The neutral merchant rank represents a measure of generalpopularity of each merchant relative to the plurality of merchants amongthe plurality of cardholders.

The MA computer system compares 716 the neutral merchant ranking vectorto the merchant ranking vector to determine a merchant score vector forthe candidate cardholder. The merchant score vector includes a merchantscore indicating the difference between the merchant rank and theneutral merchant rank associated with each merchant of the plurality ofmerchants. The merchant score represents a measure of recommendation foreach merchant of the plurality of merchants determined by the MAcomputer system for the candidate cardholder.

In the example embodiment, the MA computer system sorts 718 the merchantscore vector in descending order based on the merchant score associatedwith each merchant of the plurality of merchants. More specifically, inthe example embodiment, the merchant having the highest merchant scoreis placed first in the merchant score vector and the merchant having thelowest merchant score is placed last in the merchant score vector. Inone embodiment, the MA computer system associates a relative score witheach merchant to show each merchant's relative rank increase as relatedto the plurality of merchants. The MA computer system then provides 720a list of recommended merchants to the candidate cardholder, wherein thelist is based on the sorted merchant score vector.

FIG. 9 is a screen shot of an initial screen 900 displayed byrecommender app 119 (shown in FIG. 2 ) that may be used by a cardholder,such as a candidate cardholder, to interface with MA computer system 121(shown in FIG. 2 ). In the example embodiment, recommender app 119 isstored on cardholder computing device 118 (shown in FIG. 2 ) and is incommunication with MA computer system 121. In the example embodiment,initial screen 900 includes a “bypass authorization” selection 902 and a“connect using social network” selection 904. In the example embodiment,if candidate cardholder 22 chooses bypass authorization selection 902,then cardholder 22 is not required to enter credentials and is directedto a filter screen (shown in FIG. 10 ).

In the example embodiment, if cardholder 22 chooses connect using socialnetwork selection 904, then cardholder 22 is directed to anauthorization screen (not shown), wherein login credentials ofcardholder 22 for the social network are requested. Once authorized andlogged in, MA computer system 121 may use social network “friends” ofcardholder 22 to determine cardholder preference information forcardholder 22, as described in FIG. 7 . To use social network friends aspreferences, each friend chosen either authorizes MA computer system 121to analyze such friend's historical transaction data or registers withMA computer system 121 and manually selects preferred merchants.Cardholder 22 may either specify at least one social network friend forMA computer system 121 to analyze, or MA computer system 121 analyzesall friends of cardholder 22. Once the list of friends is determined, MAcomputer system 121 uses each selected friend's preferences to determinecardholder preference information for cardholder 22.

In the case where cardholder 22 and at least one social network friendtransact at merchant 24 together, MA computer system 121 enhances itsrecommendations by merging cardholder preference information forcardholder 22 and the preference information associated with the friend.In some embodiments, if cardholder 22 selects friends near the same ageas cardholder 22 from the list, sports bars may be ranked relativelyhigher than if, for example, the parents of cardholder 22 were selected.Moreover, a gender of cardholder 22 may also affect the listing ofmerchant recommendations. For example, if a female cardholder 22 selectsfriends of the same age, sports bars may not be ranked as highly in thelisting of merchant recommendations as they would for a male cardholder22 given all other aspects of the relative ranking determination aresimilar.

In an alternate embodiment, cardholder 22 may subscribe to at least onemerchant expert through a website or a social networking site. In suchan embodiment, cardholder preference information is determined based onmerchant ratings and/or historical transaction data associated with theexpert.

FIG. 10 is a screen shot displayed within recommender app 119 (shown inFIG. 2 ) showing a filter screen 1000 that may be used by a cardholderto interface with MA computer system 121 (shown in FIG. 2 ). Filterscreen 1000 is displayed when a cardholder chooses to bypassauthorization at initial screen 900 (shown in FIG. 9 ). Becauseauthorization was bypassed initially, candidate cardholder 22 has tomanually provide candidate cardholder preference information to MAcomputer system to receive merchant recommendations. In the exampleembodiment, filter screen 1000 includes a “scan card” selection 1002 anda “filter manually” selection 1004. In the example embodiment, ifcardholder 22 chooses filter manually selection 1004, then cardholder 22is directed to a filter manually screen 1100 (shown in FIG. 11 ).

In the example embodiment, if cardholder 22 chooses scan card selection1002, then cardholder 22 uses a camera (not shown) installed oncardholder computing device 118 (shown in FIG. 2 ) to scan the front ofa transaction card. Via recommender app 119, cardholder computing device118 transmits the scanned card data to MA computer system 121, whichuses the transaction card data to request historical transactioninformation for cardholder 22 from payment network 28 (shown in FIG. 1). In the example embodiment, historical transaction information isstored in database 120 (shown in FIG. 2 ) associated with paymentnetwork 28. MA computer system 121 uses the historical transactioninformation to determine cardholder preference information forcardholder 22, as described in FIG. 7 . In an alternate embodiment,transaction card information may be input into cardholder computingdevice 118 manually, using a magnetic stripe reader, a key fob, a touchscreen and/or any other method of inputting transaction card data into adevice that enables recommender app 119 to function as described herein.

FIG. 11 is a screen shot displayed within recommender app 119 (shown inFIG. 2 ) showing a filter manually screen 1100 that may be used by acardholder to interface with MA computer system 121 (shown in FIG. 2 ).In the example embodiment, filter manually screen 1100 displays a listof merchants 24 from which cardholder 22 chooses at least one. From theat least one selected merchant 24, MA computer system 121 determinescandidate cardholder preference information for cardholder 22, asdescribed in FIG. 7 . Although cardholder 22 must select a minimum ofone merchant 24 to enable MA computer system 121 to determine arecommendation, selecting more merchants 24 enables MA computer system121 to expand the matrix (shown in FIG. 7 ) and generate a more accurateranked list of merchants 24.

To generate the list of merchants 24, in the example embodiment, MAcomputer system 121 is programmed to determine location information ofeach of the plurality of different merchants 24 relative to apredetermined selectable location and/or a current location ofcardholder 22. For example, a cardholder that uses cardholder computingdevice 118 (shown in FIG. 2 ) having a GPS capability can use thedetermined location information to order a listing of merchants 24 bydistance from a current location of cardholder 22 or a location chosenby cardholder 22, for example, a hotel in a distant city wherecardholder 22 will be staying during an upcoming trip. In oneembodiment, cardholder 22 located in one city may order a listing ofmerchants 24 in a distant city using restaurants from a second distantcity. For example, cardholder 22 may be located in New York City andorder a listing of merchants 24 in Seattle, while basing cardholderpreference information for cardholder 22 on selections of merchants 24located in Dallas.

FIG. 12 is a screen shot displayed within recommender app 119 (shown inFIG. 2 ) showing a list 1200 of recommended merchants generated by MAcomputer system 121 (shown in FIG. 2 ). In the example embodiment, list1200 is determined using the methods described in FIG. 7 . Once therankings are determined, ranked list 1200 is formatted and displayed oncardholder computing device 118 (shown in FIG. 2 ) via recommender app119. In an alternate embodiment, ranked list 1200 is displayed tocardholder 22 on a website communicatively coupled to a network such asan intranet, WAN, or the Internet.

FIG. 13 is a screen shot displayed within recommender app 119 (shown inFIG. 2 ) showing a merchant detail screen 1300. Upon selecting amerchant from list 1200 (shown in FIG. 12 ), cardholder 22 is directedto merchant detail screen 1300 where more information about merchant 24may be displayed to cardholder 22. In the example embodiment, merchantdetail screen 1300 includes an information tab 1302, an offers tab 1304,and a loyalty tab 1306. Details from each of tabs 1302, 1304, and 1306are displayed in a display area 1308 when selected by cardholder 22.

In the example embodiment, information tab 1302 displays informationabout merchant 24 in display area 1308. For example, information tab1302 may display an address, phone number, website, hours of operation,reviews by other customers, menu or services provided, and/or any otherdesired information related to merchant 24.

In the example embodiment, offers tab 1304 displays coupons or specialoffers associated with merchant 24 in display area 1308. Merchant 24controls the offers displayed, as is described in more detail herein.The display of an offer may include details and restrictions related tothe offer, as well as an expiration date. The offer may include a barcode relating to at least one of a payment card of cardholder 22, aloyalty card, and/or details of the offer. Further, the bar code may bescanned by merchant 24 using a merchant Smartphone or the like.

In the example embodiment, loyalty tab 1306 displays loyalty and rewardsinformation associated with merchant 24 in display area 1308. In theexample embodiment, MA computer system 121 is programmed to determine aquantity of rewards points awarded to cardholder 22 based on thereceived transaction information wherein the quantity of rewards pointsis related to a combination of a transaction amount, a reward formulaassociated with merchant 24 awarding the reward points, a time of use ofthe payment card transaction, a rewards points tier of cardholder 22, arewards points special sponsored by merchant 24 awarding the rewardpoints, and a frequency of cardholder payment card transactions withmerchant 24 awarding the reward points. Additionally, MA computer system121 is programmed to recommend at least one of the plurality ofmerchants 24 that accept the payment card based on payment cardtransactions of other cardholders 22.

FIG. 14 is a screen shot of a merchant portal 1400 that interfacesbetween a merchant using client system 114 and MA computer system 121(both shown in FIG. 2 ). In the example embodiment, merchant portal 1400includes a dashboard tab 1402, a message inbox tab 1404, a charts tab1406, a customer details tab 1408, a loyalty tab 1410, and an offers tab1412.

In the example embodiment, dashboard tab 1402 displays informationregarding the business of merchant 24. More specifically, in the exampleembodiment, dashboard tab 1402 includes a new customer counter 1414configured to display an amount of new customers over a predefinedperiod of time, an active offers counter 1416 configured to display anumber of active offers merchant 24 currently has available, aredemptions counter 1418 configured to display a number of offersredeemed, and a customer counter 1420 configured to display a number ofcustomers seen during the current day.

In the example embodiment, message inbox tab 1404 enables merchant 24 tointeract with customers regarding any aspect of the business of merchant24. For example, a customer may contact merchant 24 to ask aboutredeeming an offer or coupon, to report a positive or negativeexperience, to ask directions to the place of business of merchant 24,etc.

In the example embodiment, charts tab 1406 displays various detailedcharts regarding data and statistics of merchant 24. For example, chartstab 1406 may include a chart displaying a customer traffic relationshipbetween new and existing customers, a chart displaying a number ofredemptions over a predetermined period (i.e., weekly, monthly, oryearly), a chart displaying a number new customers over a predeterminedperiod (i.e., weekly, monthly, or yearly). In some embodiments, MAcomputer system 121 generates charts relating to certain demographics ofcustomers in the area of merchant 24 and displays percentages as to howmany customers transact with merchant 24 compared to competitors ofmerchant 24.

FIG. 15 is a screen shot showing customer details tab 1408 which isaccessible through merchant portal 1400 (both shown in FIG. 14 ). In theexample embodiment, customer details tab 1408 enables merchant 24 toview and track customers that have transacted with merchant 24. Morespecifically, in the example embodiment, customer details tab 1408includes a name column 1502, a last visit column 1504, a loyalty column1506, and a status column 1508. Name column 1502 displays a list ofcustomers by name or other customer identifier. In the exampleembodiment, a cardholder having a payment card associated with paymentnetwork 28 (shown in FIG. 1 ) is automatically enrolled in all loyaltyprograms associated with all merchants 24 associated with paymentnetwork 28. Alternatively, cardholder 22 may be required toaffirmatively enroll in loyalty programs. Last visit column 1504displays the last date in which the customer visited and/or transactedwith merchant 24. Loyalty column 1506 displays an amount of loyaltyrewards the customer has received and how many are necessary to earnpoints or a gift. Status column 1508 indicates a status of the customerand may be based on at least one of an amount of money spent over apredetermined time, a number of visits to merchant 24, and/or a numberof completed transactions.

FIG. 16 is a screen shot showing loyalty tab 1410 which is accessiblethrough merchant portal 1400 (both shown in FIG. 14 ). In the exampleembodiment, loyalty tab 1410 enables merchant 24 to view, track, andcreate loyalty campaigns. An existing loyalty plans chart 1600 displaysloyalty plans currently offered by merchant 24. In the exampleembodiment, chart 1600 includes a name column 1602 that displays loyaltyplan names, a number of purchases column 1604 that displays a number ofpurchases merchant 24 has required for the customer to earn the reward,and an expiration column 1606 that displays whether the loyalty campaignexpires after a predefined period of time. Alternatively, number ofpurchases column 1604 may be substituted with any other requirement,including, but not limited to, an amount of money spent over apredetermined time and a number of visits to merchant 24.

FIG. 17 is a screen shot showing offers tab 1412 which is accessiblethrough merchant portal 1400 (both shown in FIG. 14 ). In the exampleembodiment, offers tab 1412 enables merchant 24 to view existing offersand create new offers. An existing offers chart 1700 displays offerscurrently being offered by merchant 24. In the example embodiment, chart1700 includes a name column 1702 that displays offer names, a number ofredemptions column 1704 that displays a number of times each offer hasbeen redeemed, an expiration column 1706 that displays whether theloyalty campaign expires after a predefined period of time, and anactions column 1708 that enables merchant 24 to schedule actions or editthe existing offers.

The term processor, as used herein, refers to central processing units,microprocessors, microcontrollers, reduced instruction set circuits(RISC), application specific integrated circuits (ASIC), logic circuits,and any other circuit or processor capable of executing the functionsdescribed herein.

As used herein, the terms “software” and “firmware” are interchangeable,and include any computer program stored in memory for execution by aprocessor, including RAM memory, ROM memory, EPROM memory, EEPROMmemory, and non-volatile RAM (NVRAM) memory. The above memory types areexemplary only, and are thus not limiting as to the types of memoryusable for storage of a computer program.

As will be appreciated based on the foregoing specification, theabove-described embodiments of the disclosure may be implemented usingcomputer programming or engineering techniques including computersoftware, firmware, hardware or any combination or subset thereof. Anysuch resulting program, having computer-readable code means, may beembodied or provided within one or more computer-readable media, therebymaking a computer program product, i.e., an article of manufacture,according to the discussed embodiments of the disclosure. Thecomputer-readable media may be, for example, but is not limited to, afixed (hard) drive, diskette, optical disk, magnetic tape, semiconductormemory such as read-only memory (ROM), and/or any transmitting/receivingmedium such as the Internet or other communication network or link. Thearticle of manufacture containing the computer code may be made and/orused by executing the code directly from one medium, by copying the codefrom one medium to another medium, or by transmitting the code over anetwork.

These computer programs (also known as programs, software, softwareapplications or code) include machine instructions for a programmableprocessor, and can be implemented in a high-level procedural and/orobject-oriented programming language, and/or in assembly/machinelanguage. As used herein, the terms “machine-readable storage medium”and “computer-readable storage medium” refer to any computer programproduct, apparatus and/or device (e.g., magnetic discs, optical disks,memory, Programmable Logic Devices (PLDs)) used to provide machineinstructions and/or data to a programmable processor, including amachine-readable storage medium that receives machine instructions as amachine-readable signal. The term “machine-readable signal” refers toany signal used to provide machine instructions and/or data to aprogrammable processor. The machine-readable storage medium andcomputer-readable medium do not include transitory signals.

The above-described embodiments of a method and system of rankingmerchants according to a cardholder's preferences and purchasingbehaviors provides a cost-effective and reliable means for maintainingcontact with a customer by merchants and a network interchange provider.As a result, the methods and systems described herein facilitateleveraging an payment network's assets to engage cardholders andmerchants in an enhanced purchasing experience in a cost-effective andreliable manner.

This written description uses examples to disclose the invention,including the best mode, and also to enable any person skilled in theart to practice the invention, including making and using any devices orsystems and performing any incorporated methods. The patentable scope ofthe invention is defined by the claims, and may include other examplesthat occur to those skilled in the art. Such other examples are intendedto be within the scope of the claims if they have structural elementsthat do not differ from the literal language of the claims, or if theyinclude equivalent structural elements with insubstantial differencesfrom the literal language of the claims.

What is claimed is:
 1. A computer system comprising a memory device forstoring data, and at least one processor in communication with thememory device and a payment network, the at least one processorconfigured to: receive, from the payment network, data includingelectronic payment transaction information for a plurality of electronicpayment transactions involving a plurality of accountholders including acandidate accountholder and a plurality of merchants; identify, from theelectronic payment transaction information, a subset of accountholdersfrom the plurality of accountholders, each of the subset ofaccountholders having completed electronic payment transactions with atleast two of the plurality of merchants; create, based on the electronicpayment transaction information associated with the subset ofaccountholders, a merchant popularity matrix, wherein the merchantpopularity matrix is a data structure that indicates a number oftransactions associated with the at least two merchants; apply themerchant popularity matrix to a candidate accountholder preferencevector of the candidate accountholder to create a candidateaccountholder merchant ranking vector; determine a merchant score vectorbased on a difference between the candidate accountholder merchantranking vector and a general merchant ranking vector, wherein themerchant score vector includes a merchant score associated with eachmerchant of the plurality of merchants; create a list of recommendedmerchants by sorting the merchant score vector based on the merchantscore of each merchant; and provide content configured to cause the listof recommended merchants to be displayed through an applicationexecuting on a user device of the candidate accountholder.
 2. Thecomputer system of claim 1, wherein the at least one processor isfurther configured to generate, based upon a predetermined region, asubset of the electronic payment transaction information of theplurality of electronic payment transactions involving at least some ofthe plurality of accountholders and a subset of merchants of theplurality of merchants located within the predetermined region.
 3. Thecomputer system of claim 2, wherein the at least two merchants arelocated within the predetermined region.
 4. The computer system of claim1, wherein the at least one processor is further configured to createthe merchant popularity matrix by incrementing the number oftransactions when an accountholder in the subset of accountholderscompletes multiple electronic payment transactions at the at least twomerchants, and wherein, to reduce an effect of accountholder bias towarda single merchant, the number of transactions in the merchant popularitymatrix is not incremented when the accountholder completes more than oneelectronic payment transactions at a same merchant.
 5. The computersystem of claim 1, wherein the at least one processor is furtherconfigured to: receive, from the application executing on the userdevice, input data including preference data of the candidateaccountholder, wherein the user device is in communication with theprocessor via the application, wherein the input data is entered intothe application by the candidate accountholder on the user device, andwherein the preference data represents preferences of the candidateaccountholder for particular merchants of the plurality of merchants;and determine the candidate accountholder preference vector of thecandidate accountholder based upon the received input data.
 6. Thecomputer system of claim 1, wherein the at least one processor isfurther configured to apply the merchant popularity matrix to a neutralpreference vector to create the general merchant ranking vector.
 7. Thecomputer system of claim 1, wherein the at least one processor isfurther configured to identify the plurality of merchants as registeredto use the payment network.
 8. A computer-implemented method implementedusing a computer system including a memory device for storing data, andat least one processor in communication with the memory device and apayment network, the method comprising: receiving, from the paymentnetwork, data including electronic payment transaction information for aplurality of electronic payment transactions involving a plurality ofaccountholders including a candidate accountholder and a plurality ofmerchants; identifying, from the electronic payment transactioninformation, a subset of accountholders from the plurality ofaccountholders, each of the subset of accountholders having completedelectronic payment transactions with at least two of the plurality ofmerchants; creating, based on the electronic payment transactioninformation associated with the subset of accountholders, a merchantpopularity matrix, wherein the merchant popularity matrix is a datastructure that indicates a number of transactions associated with the atleast two merchants; applying the merchant popularity matrix to acandidate accountholder preference vector of the candidate accountholderto create a candidate accountholder merchant ranking vector; determininga merchant score vector based on a difference between the candidateaccountholder merchant ranking vector and a general merchant rankingvector, wherein the merchant score vector includes a merchant scoreassociated with each merchant of the plurality of merchants; creating alist of recommended merchants by sorting the merchant score vector basedon the merchant score of each merchant; and providing content configuredto cause the list of recommended merchants to be displayed through anapplication executing on a user device of the candidate accountholder.9. The method of claim 8 further comprising generating, based upon apredetermined region, a subset of the electronic payment transactioninformation of the plurality of electronic payment transactionsinvolving at least some of the plurality of accountholders and a subsetof merchants of the plurality of merchants located within thepredetermined region.
 10. The method of claim 9, wherein the at leasttwo merchants are located within the predetermined region.
 11. Themethod of claim 8 further comprising creating the merchant popularitymatrix by incrementing the number of transactions when an accountholderin the subset of accountholders completes multiple electronic paymenttransactions at the at least two merchants, and wherein, to reduce aneffect of accountholder bias toward a single merchant, the number oftransactions in the merchant popularity matrix is not incremented whenthe accountholder completes more than one electronic paymenttransactions at a same merchant.
 12. The method of claim 8 furthercomprising: receiving, from the application executing on the userdevice, input data including preference data of the candidateaccountholder, wherein the user device is in communication with theprocessor via the application, wherein the input data is entered intothe application by the candidate accountholder on the user device, andwherein the preference data represents preferences of the candidateaccountholder for particular merchants of the plurality of merchants;and determining the candidate accountholder preference vector of thecandidate accountholder based upon the received input data.
 13. Themethod of claim 8 further comprising applying the merchant popularitymatrix to a neutral preference vector to create the general merchantranking vector.
 14. The method of claim 8 further comprising identifyingthe plurality of merchants as registered to use the payment network. 15.One or more non-transitory computer-readable storage media havingcomputer-executable instructions embodied thereon, wherein when executedby at least one processor in communication with a payment network and amemory device for storing data, the computer-executable instructionscause the at least one processor to: receive, from the payment network,data including electronic payment transaction information for aplurality of electronic payment transactions involving a plurality ofaccountholders including a candidate accountholder and a plurality ofmerchants; identify, from the electronic payment transactioninformation, a subset of accountholders from the plurality ofaccountholders, each of the subset of accountholders having completedelectronic payment transactions with at least two of the plurality ofmerchants; create, based on the electronic payment transactioninformation associated with the subset of accountholders, a merchantpopularity matrix, wherein the merchant popularity matrix is a datastructure that indicates a number of transactions associated with the atleast two merchants; apply the merchant popularity matrix to a candidateaccountholder preference vector of the candidate accountholder to createa candidate accountholder merchant ranking vector; determine a merchantscore vector based on a difference between the candidate accountholdermerchant ranking vector and a general merchant ranking vector, whereinthe merchant score vector includes a merchant score associated with eachmerchant of the plurality of merchants; create a list of recommendedmerchants by sorting the merchant score vector based on the merchantscore of each merchant; and provide content configured to cause the listof recommended merchants to be displayed through an applicationexecuting on a user device of the candidate accountholder.
 16. Thenon-transitory computer-readable storage media of claim 15, wherein thecomputer-executable instructions cause the at least one processor togenerate, based upon a predetermined region, a subset of the electronicpayment transaction information of the plurality of electronic paymenttransactions involving at least some of the plurality of accountholdersand a subset of merchants of the plurality of merchants located withinthe predetermined region.
 17. The non-transitory computer-readablestorage media of claim 15, wherein the computer-executable instructionscause the at least one processor to create the merchant popularitymatrix by incrementing the number of transactions when an accountholderin the subset of accountholders completes multiple electronic paymenttransactions at the at least two merchants, and wherein, to reduce aneffect of accountholder bias toward a single merchant, the number oftransactions in the merchant popularity matrix is not incremented whenthe accountholder completes more than one electronic paymenttransactions at a same merchant.
 18. The non-transitorycomputer-readable storage media of claim 15, wherein thecomputer-executable instructions cause the at least one processor to:receive, from the application executing on the user device, input dataincluding preference data of the candidate accountholder, wherein theuser device is in communication with the processor via the application,wherein the input data is entered into the application by the candidateaccountholder on the user device, and wherein the preference datarepresents preferences of the candidate accountholder for particularmerchants of the plurality of merchants; and determine the candidateaccountholder preference vector of the candidate accountholder basedupon the received input data.
 19. The non-transitory computer-readablestorage media of claim 15, wherein the computer-executable instructionscause the at least one processor to apply the merchant popularity matrixto a neutral preference vector to create the general merchant rankingvector.
 20. The non-transitory computer-readable storage media of claim15, wherein the computer-executable instructions cause the at least oneprocessor to identify the plurality of merchants as registered to usethe payment network.